import pandas as pd
X = pd.DataFrame({'A':[1, 2, 3], 'B':[4, 4, 4], 'C':[0, 10, 100]})
from sklearn.preprocessing import PolynomialFeatures
poly = PolynomialFeatures(include_bias=False, interaction_only=True)
X
A | B | C | |
---|---|---|---|
0 | 1 | 4 | 0 |
1 | 2 | 4 | 10 |
2 | 3 | 4 | 100 |
# Output columns: A, B, C, A*B, A*C, B*C
poly.fit_transform(X)
array([[ 1., 4., 0., 4., 0., 0.], [ 2., 4., 10., 8., 20., 40.], [ 3., 4., 100., 12., 300., 400.]])
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